class_docstr: Handler for the Vertex Google AI cloud API
docstr: Predict using the deployed model by calling the endpoint.
docstr_tok: ["Predict","using","the","deployed","model","by","calling","the","endpoint","."]
code: def predict(self, df, args=None):
      """Predict using the deployed model by calling the endpoint."""
  
      if "__mindsdb_row_id" in df.columns:
          df.drop(
              "__mindsdb_row_id", axis=1, inplace=True
          )  # TODO is this required?
  
      predict_args = self.model_storage.json_get("predict_args")
      vertex_args = self.model_storage.json_get("vertex_args")
      service_account_info = self.engine_storage.json_get(
          "service_account"
      )
  
      vertex = VertexClient(service_account_info, vertex_args)
      results = vertex.predict_from_df(
          predict_args["endpoint_name"],
          df,
          custom_model=predict_args["custom_model"],
      )
  
      if predict_args["custom_model"]:
          return pd.DataFrame(
              results.predictions, columns=[predict_args["target"]]
          )
      else:
          return pd.DataFrame(results.predictions)
  
file_path: mindsdb/mindsdb/integrations/handlers/vertex_handler/vertex_handler.py
imports: import pandas
  import json
  from mindsdb.integrations.libs.base import BaseMLEngine
  from mindsdb.integrations.handlers.vertex_handler.vertex_client import VertexClient
  from mindsdb.utilities import log
label_desc: Use image node_id 2 for calling the VertexHandler obj's underlying member method code with example usage: obj.predict(df, args) and returns: pd, pd